Distributed data-driven observer for linear time invariant systems

This paper is concerned with distributed data-driven observer design problem. The existing data-driven observers rely on a common assumption that all the information about the system, and the calculations based upon this information are centralized. Therefore the resulting algorithms cannot be applied to the distributed systems in which each local observer receives only a part of the output signal. On the other hand, traditional model-based distributed state estimation methods generally assume that the processes are decomposed according to the known process models, while in data-driven approaches there is no such information available. The main goal of this paper is to extend the centralized data-driven observer design approach to the distributed framework. The stability of the proposed data-driven distributed observer is also proved analytically. A quadruple-tank process is simulated to demonstrate the performance of the proposed scheme.     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Process noise covariance estimation via stochastic approximation

Kalman filtering for linear systems is known to provide the minimum variance estimation error, under the assumption that the model dynamics is known. While many system identification tools are available for computing the system matrices from experimental data, estimating the statistics of the output and process noises is still an open problem. Correlation-based approaches are very fast and sufficiently accurate, but there are typically restrictions on the number of noise covariance elements that can be estimated. On the other hand, maximum likelihood methods estimate all elements with high accuracy, but they are computationally expensive, and they require the use of external optimization solvers. In this paper, we propose an alternative solution, tailored for process noise covariance estimation and based on stochastic approximation and gradient-free optimization, that provides a good trade-off in terms of performance and computational load, and is also easy to implement. The effectiveness of the method as compared to the state of the art is shown on a number of recently proposed benchmark examples.     

Safety analysis of reactivity insertion accidents in a heavy water nuclear research reactor core using coupled 3D neutron kinetics thermal-hydraulic system code technique

Nuclear power plant Safety analysis using coupled 3D neutron kinetics/thermal-hydraulic codes technique is increasingly used nowadays. Actually, the use of this technique allows getting less conservatism and more realistic simulations of the physical phenomena. The challenge today is oriented toward the application of this technique to the operating conditions of nuclear research reactors. In the current study, a three-Dimensional Neutron Kinetics and best estimate Thermal-Hydraulic model based upon the coupled PARCS/RELAP5 codes has been developed and applied for a heavy water research reactor. The objective is to perform safety analysis related to design accidents of this reactor types. In the current study two positive reactivity insertion transients are considered, SCRAM protected and self-limiting power excursion cases. The results of the steady state calculations were compared with results obtained from conventional diffusion codes, while transient calculations were assessed using the point kinetic model of the RELAP5 code. Through this study, the applicability and the suitability of using the coupled code technique with respect to the classical models are emphasized and discussed.     

Structural stability of ternary D8m–Ti5Sb2X (X=Al,Ga, In,Si, Ge,Sn) compounds

The crystal and electronic structures of Ti₅Sb₂X (X=Al, Ga, In, Si, Ge, Sn) ternary compounds in the Nb₅Sn₂Si-type structure (ternary-D8_m) have been investigated by means of first principles calculations. The calculated structural parameters are in good agreement with the experimental data. The total electronic densities of states as well as the Bader charges of the atoms have been computed. Both electronic and size effects allow to explain the stability of the Ti₅Sb₂X (X=Al, Ga, In, Si, Ge, Sn) ternary compounds in the ternary D8_m structure. The enthalpies of formation of the ternary D8_m compounds have been obtained. The off-stoichiometry domains of D8_m–Ti₅Sb₂Ga and D8_m–Ti₅Sb₂Si are discussed.     

Anti‐Sway Crane Control Considering Wind Disturbance and Container Mass

A method for estimating the sway angle using an observer has already been proposed. The state observer estimates the sway angle accurately and must use the detected sway angle value. However, the estimated sway angle has an error owing to rope length error, friction force, and wind. Moreover, the container mass cannot be determined, and therefore the observer parameter is not suitable. We already proposed robust antisway control for overcoming rope length error without adding a new sensor. Further, we designed a friction disturbance observer to cancel out the influence of the friction force. In this paper, we first propose a container mass estimation method when a crane system performs rolling up control. The observer parameter can be selected using the estimated mass value. Second, in crane parallel shift control, we propose a robust antisway control even when there is a wind disturbance. We design a wind disturbance observer and propose a wind disturbance estimator to separate the friction observer output from the wind disturbance observer output. We confirm through experiments that the proposed method can reduce vibration.     

Application and validation of a statistically derived risk-based sampling plan to improve efficiency of inspection and enforcement

The statistically derived risk-based sampling plan for surveillance sample assignments of chemical and biological hazards was designed using binomial probability distribution. The binomial statistics was applied to the past 3-year data to estimate a confidence interval and a sample size aiming to improve efficiency and effectiveness of the agency's sampling and inspectional activities. The accuracy of the statistical models and computed estimates were validated in the following years. The ranges of confidence interval and sample size appeared to be significantly influenced by a level of the violation rate of feed product samples, an acceptable error, a number of the analyzed samples, and a statistical significance level. The violation rates of feed products for target analytes (aflatoxins, fumonisins, Salmonella, and dioxin) in the validation data were lower than those of the average 3-year data in most feed products. Besides, the actual violation rates of the validation samples did not exactly fall within the anticipated range of the confidence interval estimates. Such a discrepancy is considered introduced by several factors such as sample size adequacy, skewed distribution of a target analyte in feed products, and unique analyte/product combination. The overall study results indicate that the risk-based plan of work would provide a more effective and efficient risk management tool to help improve the oversight of the feed industry and the compliance to feed safety standards.     

Stability analysis of a class of fractional order nonlinear systems with order lying in (0, 2)

This paper investigates the stability of n-dimensional fractional order nonlinear systems with commensurate order 0 <α<2. By using the Mittag-Leffler function, Laplace transform and the Gronwall–Bellman lemma, one sufficient condition is attained for the local asymptotical stability of a class of fractional order nonlinear systems with order lying in (0, 2). According to this theory, stabilizing a class of fractional order nonlinear systems only need a linear state feedback controller. Simulation results demonstrate the effectiveness of the proposed theory.     

Synthesis and characterization of MgAl2O4 micro-rods by a molten salt method

Large amounts of MgAl₂O₄ micro-rods were successfully synthesized using the molten-salt technology. The effect of KCl contents on the formation of MgAl₂O₄ micro-rods was investigated. The structure and morphology of MgAl₂O₄ were investigated by means of powder X-ray diffraction, field emission scanning electron microscopy, and transmission electron microscopy, respectively. The experimental results showed that the contents of KCl significantly influenced the formation of MgAl₂O₄ micro-rods. MgAl₂O₄ micro-rods could be prepared at 1150 °C with a weight ratio of 100:1 between the salt and the starting materials. The formation of MgAl₂O₄ micro-rods could be suggested to be due to the inhomogeneous nucleation and orientated growth perpendicularly to the surfaces of Al₂O₃ grains. An impedance-type humidity sensor was finally fabricated based on the as-prepared MgAl₂O₄ micro-rods. According to tests of the humidity performance, MgAl₂O₄ micro-rods might be suitable for high-performance humidity sensors.